In the next experiment, we compare CenDE-DOBL with 12 conventional algorithms, namely gradient descent with momentum backpropagation (GDM) [1]}, gradient descent with adaptive learning rate backpropagation (GDA) [2]}, gradient descent with momentum and adaptive learning rate backpropagation (GDMA) [3]}, conjugate gradient backpropagation with Fletcher-Reeves updates (CG-FR) [4]}, conjugate gradient backpropagation with Polak-Ribiere updates (CG-PR) [5]}, [6]}, conjugate gradient backpropagation with Powell-Beale restarts (CG-PBR) [7]}, BFGS quasi-Newton backpropagation (BFGS) [8]}, Levenberg-Marquardt backpropagation (LM) [9]}, [10]}, one-step secant backpropagation (OSS) [11]}, resilient backpropagation (RP) [12]}, scaled conjugate gradient backpropagation (SCG) [13]}, and Bayesian regularisation backpropagation(BR) [14]}.
